Mina Makar

436 citations
25 papers · 327 · h-index 12

Impact in

Papers in

    • Advanced Vision and Imaging 10
    • Advanced Image and Video Retrieval Techniques 10
    • Advanced Data Compression Techniques 5
    • Image and Video Quality Assessment 5
    • Image Retrieval and Classification Techniques 5
    • Robotics and Sensor-Based Localization 8

Mina Makar

24 papers receiving 312 citations

Peers

Mina Makar
Comparison fields: 5 of 28
  • Computer Vision and Pattern Recognition 284
  • Computer Graphics and Computer-Aided Design 29
  • Signal Processing 37
  • Aerospace Engineering 66
  • Computer Networks and Communications 37
Replace Akash Kushal with:
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Mina Makar relative to Akash Kushal United States Akash Kushal's profile →
Citations per field
00.5×6.4×
Akash Kushal · 1×
Citations per year

Countries citing papers authored by Mina Makar

Since Specialization
Citations

This map shows the geographic impact of Mina Makar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mina Makar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mina Makar more than expected).

Fields of papers citing papers by Mina Makar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mina Makar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mina Makar. The network helps show where Mina Makar may publish in the future.

Co-authors

The 22 scholars most cited alongside Mina Makar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mina Makar Line = papers co-authored together Mina Makar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200551
2 200938
3 201836
4 201428
5 201320
6 201017
7 201417
8 200716
9 201215
10 201214
11 201413
12 201011
13 201410
14 20129
15 20098
16 20078
17 20064
18 20113
19 20043
20 20092

About Mina Makar

Mina Makar is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Computer Networks and Communications, Signal Processing and Artificial Intelligence, having authored 25 papers that have together received 327 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (10 papers), Advanced Image and Video Retrieval Techniques (10 papers), Robotics and Sensor-Based Localization (8 papers), Advanced Data Compression Techniques (5 papers), Image and Video Quality Assessment (5 papers), Image Retrieval and Classification Techniques (5 papers), Video Coding and Compression Technologies (4 papers) and Wireless Communication Networks Research (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (284 citations), Computer Graphics and Computer-Aided Design (29 citations), Signal Processing (37 citations), Aerospace Engineering (66 citations) and Computer Networks and Communications (37 citations). Mina Makar has collaborated with scholars based in United States, United Kingdom and Egypt. Frequent co-authors include Bernd Girod, Hassan M. Elkamchouchi, Sam S. Tsai, Vijay Chandrasekhar, David Chen, Chuo-Ling Chang, David M. Chen, Hassan M. Elragal, André Araujo and Thomas Neff. Their work appears in journals such as IEEE Transactions on Image Processing, ACM Transactions on Graphics, International Journal of Semantic Computing, Cureus and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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